The automated, fully 3D whole-brain segmentation procedure(Fischl et al. 2002; Fischl et al. 2004) in FreeSurfer uses a probabilistic atlas and applies a Bayesian classification rule to assign a neuroanatomical label to each voxel. The atlas consists of a manually-derived training set created by the Center for Morphometric Analysis (http://www.cma.mgh.harvard.edu/) from 20 unrelated, randomly selected VETSA participants. The accuracy of a previously used training atlas has been shown to be comparable to that of expert manual labeling and is sensitive to subtle brain changes in Alzheimer's disease and normal aging (Fischl et al. 2002; Fischl et al. 2004). Manual labeling for the VETSA-specific atlas and the previously used atlas was performed by the same laboratory at the Center for Morphometric Analysis. When both were compared with expert manual labeling, the VETSA- specific atlas was shown to be more accurate than the previously used training atlas in this sample (Kremen et al. 2010).
